The Real Risk in an Algo-Driven Market

Larry Benedict
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Apr 22, 2026
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Trading With Larry Benedict
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3 min read

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With the stock market’s huge recovery from its March 30 lows, you might assume we’re back in rally mode. After all, the bull market is now well into its fourth year.

But the rally’s foundation may not be as sturdy as you’d think.

Algorithmic (algo) trading has driven a big part of that rally. That broadly encompasses any systematic or rules-based strategy where computer programs buy and sell based on predefined rules or models.

So rather than buying a stock based on a fundamental valuation, for example, these models typically react to data points, such as a sharp rise in volume, price, or volatility or the movement of correlated stocks.

Because these models are often looking at the same sets of data, they can end up jumping onto the same trade, causing exaggerated moves.

That might be welcome for investors when stocks are rallying strongly. But it can be bruising if things go the other way…

An Algo Feedback Loop

The rally over the last few weeks shows just how powerful algo trading has become.

One common algo strategy is to capture rising momentum. Once buying momentum took hold after the March 30 low, other momentum-tracking algos jumped into the trade. This became a feedback loop, causing stocks to rally sharply.

In just 13 days, the S&P 500 and Nasdaq gained 12.8% and 16.8%, respectively, smashing out a series of new all-time highs.

Yet against that backdrop, the conflict in the Middle East is dragging on. Plus, rising inflation data has been fueling fears about interest rates remaining higher for longer – or even a rate hike coming into play.

Those threats clearly aren’t being factored in, at least in the short-term. Markets haven’t been riding higher based on fundamental factors.

All that rampant action comes from order flow and funds’ repositioning according to their models. The buying was due to the mechanics of those algos, causing stock prices to rally.

The problem arises when momentum suddenly switches and all those algos react the same way…

The Feedback Loop Unwinds

Eventually, algo-based funds will reach their maximum allowable exposure to any position and/or start taking profits. In algo trading, quick, sharp profits are highly prized.

So once stock prices start to stall, those momentum models can quickly unwind.

Another catalyst can be a rise in volatility, which can force funds to offload positions to reduce risk – triggering a wave of selling across the board.

What looked like a strong and steady up move can reverse in the blink of an eye. Strictly speaking, there doesn’t need to be a news-based event to set off a wave of selling – just enough of a shift to trigger a response in the algo models.

And as the rally feeds off its own feedback loop, selling can accelerate as those models all react to the same data points. This effect is magnified when shifts in momentum, volatility, and price occur at the same time.

That’s why it’s so important as a trader not to become beholden to the news cycle or your own assumptions about how the stock market should act.

Instead, keep a close watch on factors that drive algo trading – like momentum and volatility – and how they’re moving in real time.

Because these shifts often determine the market’s next move.

Happy Trading,

Larry Benedict
Editor, Trading With Larry Benedict


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